Algorithmic Trading is an approach that leverages algorithms to implement trading activities. Algorithms help develop models and train them to analyse parameters like time, price, and volume. Algorithmic trading offers efficiency by combining speed and computational resources.
We present you the Top Algorithmic Trading blogs written by our domain experts. These blogs cater to various levels from basics to intermediate and advanced. The blogs also include guides, tutorials, etc. to help you learn more about Algorithmic Trading.
Algorithmic Trading: What it is, How to Start, Strategies, and More
The blog is a complete beginner's guide that explains the basic terms of algorithmic trading. The advancement in technology and domain algorithms is taking trading activities to the next level. The article discusses:
- What and Why of Algorithmic Trading?
- The Transformation from Manual to Algo Trading
- When did Algorithmic Trading start?
- Algo Trading Strategies
- Algorithmic Trading Salaries
- What are the Rules and Regulations in India?
- How to Learn Algorithmic Trading
- The workflow of Algorithmic Trading
- How to build your own Algorithmic Trading Business?
Free Resources to Learn Algorithmic Trading
This blog covers a comprehensive and robust compiled list of resources you can access for free. Resources like books, tutorials, webinar recordings, python tutorials, etc. are completely accessible for you to use and learn from. It is a great way for beginners to enter the world of algorithmic trading.
Algorithmic Trader Vs Quant Developer
As the name suggests, the article gives a comparison between an algorithmic trader and a quant developer. Both are individually relevant in the domain of algorithmic trading when combined together.
The article explains:
- What are an algorithmic trader and a quant developer?
- What is the salary of an algorithmic trader and a quant developer?
- Educational Qualifications
- The difference in the job roles of an algorithmic trader and a quant developer
Making a Career in Algorithmic Trading
We are sure you are curious to know:
- How to prepare for a career in algorithmic trading?
- How to establish your journey in quantitative finance?
- How do you change your career trajectory to Algorithmic Trading?
- How and where to begin?
The field of algo trading opens up several avenues for individuals. Want to know the various opportunities you can grab in this field? Learn about the various jobs, career opportunities, skill requirements, qualifications, salaries etc. offered within the domain in this blog.
Why You Should Invest In Algorithmic Trading?
Being a popular phenomenon, the domain of algorithmic trading helps traders effectively implement trading activities. It helps develop strategies and models that automate tasks with speed and accuracy. By getting into the domain as a beginner, individuals may be more curious. This blog takes you through 5 pivotal reasons why you should invest in algo trading!
Tips From Experienced Algorithmic Trading Practitioners
Do you wish to learn and grow in the field of algorithmic trading? Want to know what are the best practices successful traders use? We present a blog created that walks you through the practical approaches taken by practitioners. Learn from experienced practitioners at QuantInsti.
Why do You Face Obstacles In Learning Algorithmic Trading?
When you shift to the domain of algo trading you may face certain challenges or obstacles while learning and developing skills. The article discusses various obstacles you may face and the solutions you can use to overcome the same.
How Algorithmic Trading Can Keep You Out of Trouble?
Algo trading definitely saves time, cost and effort. The right knowledge and resources used in algorithmic trading can help increase your horizons. This article discusses common troubles and solutions to them and the frequently asked questions.
Myths vs. Reality of Algorithmic Trading
Algorithmic trading is not as complex as it sounds! Algorithms in trading can offer you reliable, accurate, and quick trading solutions. Want to become a successful algo trader? This blog debunks the various myths, discusses suitable skills, and provides multiple successful stories!
Types of Trading Strategies: Components, Methods, and More
There are multiple strategies within algorithmic trading that cater to various purposes. While implementing the right strategy traders can execute trades with accuracy and effectiveness. The article offers a broad understanding of the various strategies that traders could apply.
The article explains:
- What is a trading strategy?
- Components of a trading strategy
- Types of trading strategies
- ML-based trading strategies
- Portfolio of strategies
Special mentions
Machine Learning Classification Algorithms
The blog simply covers the Machine Learning Classification requirements and briefly discusses:
- Supervised Learning
- Unsupervised Learning
- Types of Supervised Models
- Types of Classification
- Classifier Models
- Hyperparameter Tuning
- Performance Evaluation
- Using SVC for Trading
- Resources to Learn Machine Learning
Stock Market Math: Essential Concepts for Algorithmic Trading
Have you ever wondered, why do we need to understand and learn about Stock Market Math?
You may have pondered upon questions like:
- What is the need of learning Math for stock markets?
- Where do I learn about the application of math in the stock markets?
- What are the basics of stock market math?
This blog discusses the mathematics and statistics in stock trading which is also known as stock market math.
Qualities of a Successful Algorithmic Trader
The domain of algo trading offers a multitude of opportunities to individuals. The more you develop your skills in the domain the more you can build a successful career. This article simply discusses the best qualities of a successful algo trader.
You can read more about 5 Things to know before starting Algorithmic Trading
Disclaimer: All data and information provided in this article are for informational purposes only. QuantInsti® makes no representations as to accuracy, completeness, currentness, suitability, or validity of any information in this article and will not be liable for any errors, omissions, or delays in this information or any losses, injuries, or damages arising from its display or use. All information is provided on an as-is basis.
